.Rhistory

split.set <- read.csv(separate_tri.csv)
split.set <- read.csv(datasets/separate_tri.csv)
split.set <- read.csv("datasets/separate_tri.csv")
original_set <- read.csv("aa_trinomials_1.csv")
original_set <- read.csv("datasets/aa_trinomials_1.csv")
attach(original.set)
attach(split.set)
attach(original_set)
(tri_data_split <- data.frame(
title = Title,
year = Year,
volnum = Volume.Number,
issuenum = Issue.Number,
pagenum = Page.Number,
primauth = Primary.Author.s.Last.Name,
tri_instance = Trinomial.Instance,
st = state,
ct = county,
site = row,
jstor = JSTOR.LINK,
ststring = State,
ctstring = County,
comm = Comments,
avoid = Avoid..H.M.L.
))
tri_data_split$fulltri <- paste(st, ct, site, sep="")
View(tri_data_split)
View(tri_data_split)
tri_data_split$fulltri <- paste(tri_data_split$st, ct, site, sep="")
# Add full combined trinomial back to the data set.
attach(tri_data_split)
tri_data_split$fulltri <- paste(st, ct, site, sep="")
detach(tri_data_split)
detach(split.set)
detach(original_set)
View(tri_data_split)
attach(tri_data_split)
tri_cleaned <- subset(tri_data_split, ct != "NA", ct != "ML")
detach(tri_data_split)
write.csv("DINAA-AA_Trinomials_Split_Cleaned_2.csv")
write.csv(tri_data_split, "DINAA-AA_Trinomials_Split_Cleaned_2.csv")